Noninvasive Assessment of Tumor Histological Grade in Invasive Breast Carcinoma Based on Ultrasound Radiomics and Clinical Characteristics: A Multicenter Study.

Rationale and Objectives: We aimed to develop and validate prediction models for histological grade of invasive breast carcinoma (BC) based on ultrasound radiomics features and clinical characteristics. Materials and Methods: A number of 383 patients with invasive BC were retrospectively enrolled and divided into a training set (207 patients), internal validation set (90 patients), and external validation set (86 patients). Ultrasound radiomics features were extracted from all the eligible patients. The Boruta method was used to identify the most useful features. Seven classifiers were adopted to developed prediction models. The output of the classifier with best performance was labeled as the radiomics score (Rad-score) and the classifier was selected as the Rad-score model. A combined model combining clinical factors and Rad-score was developed. The performance of the models was evaluated using receiver operating characteristic curve. Results: Seven radiomics features were selected from 788 candidate features. The logistic regression model performing best among the 7 classifiers in the internal and external validation sets was considered as Rad-score model, with areas under the receiver operating characteristic curve (AUC) values of 0.731 and 0.738. The tumor size was screened out as the risk factor and the combined model was developed, with AUC values of 0.721 and 0.737 in the internal and external validation sets. Furthermore, the 10-fold cross-validation demonstrated that the 2 models above were reliable and stable. Conclusion: The Rad-score model and combined model were able to predict histological grade of invasive BC, which may enable tailored therapeutic strategies for patients with BC in routine clinical use.

Translational and Therapeutic Evaluation of RAS-GTP Inhibition by RMC-6236 in RAS-Driven Cancers.

RAS-driven cancers comprise up to 30% of human cancers. RMC-6236 is a RAS(ON) multi-selective noncovalent inhibitor of the active, GTP-bound state of both mutant and wild-type variants of canonical RAS isoforms with broad therapeutic potential for the aforementioned unmet medical need. RMC-6236 exhibited potent anticancer activity across RAS-addicted cell lines, particularly those harboring mutations at codon 12 of KRAS. Notably, oral administration of RMC-6236 was tolerated in vivo and drove profound tumor regressions across multiple tumor types in a mouse clinical trial with KRASG12X xenograft models. Translational PK/efficacy and PK/PD modeling predicted that daily doses of 100 mg and 300 mg would achieve tumor control and objective responses, respectively, in patients with RAS-driven tumors. Consistent with this, we describe here objective responses in two patients (at 300 mg daily) with advanced KRASG12X lung and pancreatic adenocarcinoma, respectively, demonstrating the initial activity of RMC-6236 in an ongoing phase I/Ib clinical trial (NCT05379985). SIGNIFICANCE: The discovery of RMC-6236 enables the first-ever therapeutic evaluation of targeted and concurrent inhibition of canonical mutant and wild-type RAS-GTP in RAS-driven cancers. We demonstrate that broad-spectrum RAS-GTP inhibition is tolerable at exposures that induce profound tumor regressions in preclinical models of, and in patients with, such tumors. This article is featured in Selected Articles from This Issue, p. 897.

Concurrent inhibition of oncogenic and wild-type RAS-GTP for cancer therapy.

RAS oncogenes (collectively NRAS, HRAS and especially KRAS) are among the most frequently mutated genes in cancer, with common driver mutations occurring at codons 12, 13 and 611. Small molecule inhibitors of the KRAS(G12C) oncoprotein have demonstrated clinical efficacy in patients with multiple cancer types and have led to regulatory approvals for the treatment of non-small cell lung cancer2,3. Nevertheless, KRASG12C mutations account for only around 15% of KRAS-mutated cancers4,5, and there are no approved KRAS inhibitors for the majority of patients with tumours containing other common KRAS mutations. Here we describe RMC-7977, a reversible, tri-complex RAS inhibitor with broad-spectrum activity for the active state of both mutant and wild-type KRAS, NRAS and HRAS variants (a RAS(ON) multi-selective inhibitor). Preclinically, RMC-7977 demonstrated potent activity against RAS-addicted tumours carrying various RAS genotypes, particularly against cancer models with KRAS codon 12 mutations (KRASG12X). Treatment with RMC-7977 led to tumour regression and was well tolerated in diverse RAS-addicted preclinical cancer models. Additionally, RMC-7977 inhibited the growth of KRASG12C cancer models that are resistant to KRAS(G12C) inhibitors owing to restoration of RAS pathway signalling. Thus, RAS(ON) multi-selective inhibitors can target multiple oncogenic and wild-type RAS isoforms and have the potential to treat a wide range of RAS-addicted cancers with high unmet clinical need. A related RAS(ON) multi-selective inhibitor, RMC-6236, is currently under clinical evaluation in patients with KRAS-mutant solid tumours (ClinicalTrials.gov identifier: NCT05379985).

Passively Q-switched Nd3+ solid-state lasers with hexakis-[(trimethylsilyl)ethynyl]benzene and graphdiyne as saturable absorbers.

In this paper, two-dimensional Graphdiyne and Hexakis-[(trimethylsilyl)ethynyl]benzene nanosheets were prepared using the liquid-phase exfoliation method and were then successfully applied to 1.06 µm passively Q-Switched all-solid-state lasers. The Hexakis-[(trimethylsilyl)ethynyl]benzene was applied for the first time in passively Q-Switched all-solid-state lasers, as we know. For Graphdiyne, the Q-Switched pulse achieved a narrowest pulse width of 415 ns, a maximum repetition frequency of 244.2 kHz, a maximum pulse energy of 133.53 nJ, and peak power of 321.77 mW was obtained. While, the narrowest pulse width, maximum repetition frequency, maximum pulse energy, and peak power for Hexakis-[(trimethylsilyl)ethynyl]benzene are approximately 398.4 ns, 297.1 kHz, 89.61 nJ, and 220.39 mW respectively. The findings demonstrate the promising potential of both candidates as saturable absorbers for signal modulation in solid-state lasers.

Pyroptosis and the tumor immune microenvironment: A new battlefield in ovarian cancer treatment.

Ovarian cancer is a less common tumor in women compared to cervical or breast cancer, however it is more malignant and has worse outcomes. Ovarian cancer patients still have a five-year survival rate < 50% despite advances in therapy. Due to recent developments in immune checkpoint inhibitors (ICIs), cancer immunotherapy has attracted increased interest. Pyroptosis is a highly inflammatory form of cell death, which is essential for bridging innate and adaptive immunity, and is involved in immune regulation within the tumor microenvironment (TME). Recent research has shown that pyroptosis can promote immunotherapy of ovarian cancer, including treatment with chimeric antigen receptor T-cells (CAR-T) or ICIs. Moreover, inflammasomes, various signaling pathways and lncRNAs can all affect pyroptosis in ovarian cancer. Here we discuss how pyroptosis affects the development and progression of ovarian cancer as well as the TME. We also provide a summary of small molecule drugs that could target pyroptotic cell death processes and may be useful in ovarian cancer therapy.

Tumor-selective effects of active RAS inhibition in pancreatic ductal adenocarcinoma.

Broad-spectrum RAS inhibition holds the potential to benefit roughly a quarter of human cancer patients whose tumors are driven by RAS mutations. However, the impact of inhibiting RAS functions in normal tissues is not known. RMC-7977 is a highly selective inhibitor of the active (GTP-bound) forms of KRAS, HRAS, and NRAS, with affinity for both mutant and wild type (WT) variants. As >90% of human pancreatic ductal adenocarcinoma (PDAC) cases are driven by activating mutations in KRAS, we assessed the therapeutic potential of RMC-7977 in a comprehensive range of PDAC models, including human and murine cell lines, human patient-derived organoids, human PDAC explants, subcutaneous and orthotopic cell-line or patient derived xenografts, syngeneic allografts, and genetically engineered mouse models. We observed broad and pronounced anti-tumor activity across these models following direct RAS inhibition at doses and concentrations that were well-tolerated in vivo. Pharmacological analyses revealed divergent responses to RMC-7977 in tumor versus normal tissues. Treated tumors exhibited waves of apoptosis along with sustained proliferative arrest whereas normal tissues underwent only transient decreases in proliferation, with no evidence of apoptosis. Together, these data establish a strong preclinical rationale for the use of broad-spectrum RAS inhibition in the setting of PDAC.

Resection of intracardiac leiomyoma originating from the inferior vena cava through a single median sternotomy incision using a silk suture snare technique: a case report.

BACKGROUND: Intracardiac leiomyoma is a rare benign right heart tumor that usually extends from the intravenous system. The patient often has a history of uterine leiomyoma. CASE PRESENTATION: We report a 46-year-old female patient who presented to us with exertional dyspnea, chest tightness, and shortness of breath for two weeks and had a history of uterine leiomyoma resection. Echocardiography showed a pedunculated solid mass in the right heart with the pedicle attached to the inferior vena cava. The surgery was performed under cardiopulmonary bypass established through the femoral artery and vein with a probable diagnosis of leiomyoma. The tumor was removed by ingenious surgical technique: a snare made of silk suture in which the tumor's pedicle was trapped, and the tumor with its pedicle was carefully removed with the help of a scalpel along the silk suture. The histopathology report confirmed the diagnosis of intravenous leiomyoma. The postoperative course was uneventful and the patient was discharged a week later. CONCLUSION: Intracardiac leiomyoma is a rare benign smooth muscle tumor. Surgery is the mainstay of treatment with different surgical approaches available. It is possible to completely remove cardiac leiomyomas through sternotomy without the need for an abdominal incision if the leiomyoma is originated in the inferior vena cava not far from the right atrium.

Comparison of machine learning models based on multi-parametric magnetic resonance imaging and ultrasound videos for the prediction of prostate cancer.

Objective: To establish machine learning (ML) prediction models for prostate cancer (PCa) using transrectal ultrasound videos and multi-parametric magnetic resonance imaging (mpMRI) and compare their diagnostic performance. Materials and methods: We systematically collated the data of 383 patients, including 187 with PCa and 196 with benign lesions. Of them, 307 patients (150 with PCa and 157 with benign lesions) were randomly selected to train and validate the ML models, 76 patients were used as test set. B-Ultrasound videos (BUS), mpMRI T2 sequence (T2), and ADC sequence (ADC) were obtained from all patients. We extracted 851 features of each patient in the BUS, T2, and ADC groups and used a t-test, the Mann-Whitney U test, and LASSO regression to screen the features. Support vector machine (SVM), random forest (RF), adaptive boosting (ADB), and gradient boosting machine (GBM) models were used to establish radiomics models. In addition, we fused the features screened via LASSO regression from three groups as new features and rebuilt ML models. The performance of the ML models in diagnosing PCa in the BUS, T2, ADC, and fusion groups was compared using the area under the ROC curve (AUC), sensitivity, specificity, and accuracy. Results: In the test cohort, the AUC of each model in the ADC group was higher than that of in the.BUS and T2 groups. Among the models, the RF model had the best diagnostic performance, with an AUC of 0.85, sensitivity of 0.78 (0.61-0.89), specificity of 0.84 (0.69-0.94), and accuracy of 0.83 (0.66-0.93). The SVM model in both the BUS and T2 groups performed best. Based on the features screened in the BUS, T2, and ADC groups fused to construct the models, the SVM model was found to perform best, with an AUC of 0.87, sensitivity of 0.73 (0.56-0.86), specificity of 0.79 (0.63-0.90), and accuracy of 0.77 (0.59-0.89). The difference in the results was statistically significant (p<0.05). Conclusion: The ML prediction models had a good diagnostic ability for PCa. Among them, the SVM model in the fusion group showed the best performance in diagnosing PCa. These prediction models can help radiologists make better diagnoses.

Value of machine learning-based transrectal multimodal ultrasound combined with PSA-related indicators in the diagnosis of clinically significant prostate cancer.

Objective: To investigate the effect of transrectal multimodal ultrasound combined with serum prostate-specific antigen (PSA)-related indicators and machine learning for the diagnosis of clinically significant prostate cancer. Methods: Based on Gleason score of postoperative pathological results, the subjects were divided into clinically significant prostate cancer groups(GS>6)and non-clinically significant prostate cancer groups(GS ≤ 6). The independent risk factors were obtained by univariate logistic analysis. Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) machine learning models were combined with clinically significant prostate cancer risk factors to establish the machine learning model, calculate the model evaluation indicators, construct the receiver operating characteristic curve (ROC), and calculate the area under the curve (AUC). Results: Independent risk factor items (P< 0.05) were entered into the machine learning model. A comparison of the evaluation indicators of the model and the area under the ROC curve showed the ANN model to be best at predicting clinically significant prostate cancer, with a sensitivity of 80%, specificity of 88.6%, F1 score of 0.897, and the AUC was 0.855. Conclusion: Establishing a machine learning model by rectal multimodal ultrasound and combining it with PSA-related indicators has definite application value in predicting clinically significant prostate cancer.

Development of Clioquinol Platinum(IV) Conjugates as Autophagy-Targeted Antimetastatic Agents.

A series of autophagy-targeted antimetastatic clioquinol (CLQ) platinum(IV) conjugates were designed and prepared by incorporating an autophagy activator CLQ into the platinum(IV) system. Complex 5 with the cisplatin core bearing dual CLQ ligands with potent antitumor properties was screened out as a candidate. More importantly, it displayed potent antimetastatic properties both in vitro and in vivo as expected. Mechanism investigation manifested that complex 5 induced serious DNA damage to increase γ-H2AX and P53 expression and caused mitochondria-mediated apoptosis through the Bcl-2/Bax/caspase3 pathway. Then, it promoted prodeath autophagy by suppressing PI3K/AKT/mTOR signaling and activating the HIF-1α/Beclin1 pathway. The T-cell immunity was elevated by restraining the PD-L1 expression and subsequently increasing CD3+ and CD8+ T cells. Ultimately, metastasis of tumor cells was suppressed by the synergistic effects of DNA damage, autophagy promotion, and immune activation aroused by CLQ platinum(IV) complexes. Key proteins VEGFA, MMP-9, and CD34 tightly associated with angiogenesis and metastasis were downregulated.

Systemic inflammation with sarcopenia predicts survival in patients with gastric cancer.

OBJECTIVE: The levels of platelet-related inflammation indicators and sarcopenia have been reported to affect the survival of patients with cancer. To evaluate the prognostic influence of platelet count (PLT), platelet lymphocyte ratio (PLR), and systemic immune inflammation index (SII), and SII combined with sarcopenia on the survival of patients with gastric cancer (GC). METHODS: A total of 1133 patients with GC (812 male and 321 female, average age: 59.43 years) were evaluated. Receiver-operating characteristic curves were used to determine the best cutoff values of PLT, PLR, and SII, and univariate and multivariate Cox risk regression models were used to evaluate whether SII is an independent predictor of overall survival (OS). The prognostic SS (SII-sarcopenia) was established based on SII and sarcopenia. Finally, a comprehensive analysis of the prognostic SS was performed. RESULTS: SII had the strongest prognostic effect. The SII and OS of patients with GC were in an inverted U-shape (adjusted HR = 1.07; 95% CI 0.97-1.19; adjusted P = 0.179). In patients with SII > 1800, SII was negatively correlated with OS (adjusted HR = 0.57; 95% CI 0.29-1.12; adjusted P = 0.102), however, there is no statistical difference. Interestingly, a high SS was associated with a poorer prognosis. The higher the SS score was, the worse the OS (P < 0.001). CONCLUSION: SII is an independent prognostic indicator of GC, and high SII is related to poor prognosis. A higher SS score had worse survival. Thus, the prognostic SS is a reliable predictor of OS in patients with GC.

Discovery of RMC-5552, a Selective Bi-Steric Inhibitor of mTORC1, for the Treatment of mTORC1-Activated Tumors.

Hyperactivation of mTOR kinase by mutations in the PI3K/mTOR pathway or by crosstalk with other mutant cancer drivers, such as RAS, is a feature of many tumors. Multiple allosteric inhibitors of mTORC1 and orthosteric dual inhibitors of mTORC1 and mTORC2 have been developed as anticancer drugs, but their clinical utility has been limited. To address these limitations, we have developed a novel class of "bi-steric inhibitors" that interact with both the orthosteric and the allosteric binding sites in order to deepen the inhibition of mTORC1 while also preserving selectivity for mTORC1 over mTORC2. In this report, we describe the discovery and preclinical profile of the development candidate RMC-5552 and the in vivo preclinical tool compound RMC-6272. We also present evidence that selective inhibition of mTORC1 in combination with covalent inhibition of KRASG12C shows increased antitumor activity in a preclinical model of KRASG12C mutant NSCLC that exhibits resistance to KRASG12C inhibitor monotherapy.

Development and validation of an ultrasound-based radiomics nomogram for predicting the luminal from non-luminal type in patients with breast carcinoma.

Introduction: The molecular subtype plays a significant role in breast carcinoma (BC), which is the main indicator to guide treatment and is closely associated with prognosis. The aim of this study was to investigate the feasibility and efficacy of an ultrasound-based radiomics nomogram in preoperatively discriminating the luminal from non-luminal type in patients with BC. Methods: A total of 264 BC patients who underwent routine ultrasound examination were enrolled in this study, of which 184 patients belonged to the training set and 80 patients to the test set. Breast tumors were delineated manually on the ultrasound images and then radiomics features were extracted. In the training set, the T test and least absolute shrinkage and selection operator (LASSO) were used for selecting features, and the radiomics score (Rad-score) for each patient was calculated. Based on the clinical risk features, Rad-score, and combined clinical risk features and Rad-score, three models were established, respectively. The performances of the models were validated with receiver operator characteristic (ROC) curve and decision curve analysis. Results: In all, 788 radiomics features per case were obtained from the ultrasound images. Through radiomics feature selection, 11 features were selected to constitute the Rad-score. The area under the ROC curve (AUC) of the Rad-score for predicting the luminal type was 0.828 in the training set and 0.786 in the test set. The nomogram comprising the Rad-score and US-reported tumor size showed AUCs of the training and test sets were 0.832 and 0.767, respectively, which were significantly higher than the AUCs of the clinical model in the training and test sets (0.691 and 0.526, respectively). However, there was no significant difference in predictive performance between the Rad-score and nomogram. Conclusion: Both the Rad-score and nomogram can be applied as useful, noninvasive tools for preoperatively discriminating the luminal from non-luminal type in patients with BC. Furthermore, this study might provide a novel technique to evaluate molecular subtypes of BC.

Multi-specific niflumic acid platinum(IV) complexes displaying potent antitumor activities by improving immunity and suppressing angiogenesis besides causing DNA damage.

To develop new chemotherapeutics with anti-metastasis properties, a series of multi-specific niflumic acid (NFA) platinum(IV) complexes with DNA damage, inflammation inhibition, immunity activation, and angiogenesis suppression mechanisms were designed, synthesized and evaluated as novel antitumor agents. The dual NFA platinum(IV) complex with a cisplatin core showed promising antitumor activities both in vitro and in vivo with lower toxicity than platinum(II) drugs and displayed attractive anti-metastasis performance. It caused serious DNA damage and further elevated the expression of γ-H2AX. Furthermore, it promoted apoptosis by activating the mitochondrial apoptotic pathway and autophagy of tumor cells. Moreover, immune response in tumors was significantly improved by increasing CD3+, CD4+ and CD8+ T infiltrating cells. Subsequently, the pathway ERK/HIF-1α/VEGFA associated with angiogenesis was suppressed by the reduced inflammation and elevated immune response, and the density of microvessels marked by CD34 was significantly reduced in tumors. Accordingly, the multi-specific NFA platinum(IV) complexes have great potential to be developed as novel anti-proliferative and anti-metastatic drugs.

Integration of ultrasound radiomics features and clinical factors: A nomogram model for identifying the Ki-67 status in patients with breast carcinoma.

Objective: The aim of this study was to develop and validate an ultrasound-based radiomics nomogram model by integrating the clinical risk factors and radiomics score (Rad-Score) to predict the Ki-67 status in patients with breast carcinoma. Methods: Ultrasound images of 284 patients (196 high Ki-67 expression and 88 low Ki-67 expression) were retrospectively analyzed, of which 198 patients belonged to the training set and 86 patients to the test set. The region of interest of tumor was delineated, and the radiomics features were extracted. Radiomics features underwent dimensionality reduction analysis by using the independent sample t test and least absolute shrinkage and selection operator (LASSO) algorithm. The support vector machine (SVM), logistic regression (LR), decision tree (DT), random forest (RF), naive Bayes (NB) and XGBoost (XGB) machine learning classifiers were trained to establish prediction model based on the selected features. The classifier with the highest AUC value was selected to convert the output of the results into the Rad-Score and was regarded as Rad-Score model. In addition, the logistic regression method was used to integrate Rad-Score and clinical risk factors to generate the nomogram model. The leave group out cross-validation (LGOCV) method was performed 200 times to verify the reliability and stability of the nomogram model. Results: Six classifier models were established based on the 15 non-zero coefficient features. Among them, the LR classifier achieved the best performance in the test set, with the area under the receiver operating characteristic curve (AUC) value of 0.786, and was obtained as the Rad-Score model, while the XGB performed the worst (AUC, 0.615). In multivariate analysis, independent risk factor for high Ki-67 status was age (odds ratio [OR] = 0.97, p = 0.04). The nomogram model based on the age and Rad-Score had a slightly higher AUC than that of Rad-Score model (AUC, 0.808 vs. 0.798) in the test set, but no statistical difference (p = 0.144, DeLong test). The LGOCV yielded a median AUC of 0.793 in the test set. Conclusions: This study proposed a convenient, clinically useful ultrasound radiomics nomogram model that can be used for the preoperative individualized prediction of the Ki-67 status in patients with BC.

Diagnostic performance of elastosonography in the differential diagnosis of benign and malignant salivary gland tumors: A meta-analysis.

Purpose: The clinical practice of elastosonography for the detection of salivary gland tumors is still a controversial issue. The objective of this meta-analysis was to evaluate the effect of elastosonography for the diagnosis of salivary gland tumors and to compare the diagnostic value of elastosonography and conventional ultrasound in the diagnosis of salivary gland tumors. Methods: A comprehensive literature search through PubMed, EMBASE, and Cochrane Library was carried out from inception to November 2021. Two researchers independently extracted the data from the enrolled papers using a standard data extraction form. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated to evaluate the diagnostic performance of elastosonography. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was utilized to evaluate the quality of each included study. Meta-DiSc version 1.4, Review Manager 5.3, and StataSE 15 were used. Results: Sixteen studies with a total of 1105 patients with 1146 lesions were included in this meta-analysis. The pooled sensitivity, specificity, PLR, NLR, and DOR of elastosonography for the differentiation between benign and malignant salivary gland tumors were 0.73 (95%CI, 0.66-0.78), 0.64 (95%CI, 0.61-0.67), 2.83 (95%CI, 1.97-4.07), 0.45 (95%CI, 0.32-0.62), and 9.86 (95%CI, 4.49-21.62), respectively, with an AUC of 0.82. Four studies provided data regarding the conventional ultrasound for the differentiation between benign and malignant salivary gland tumors. The pooled sensitivity, specificity, and DOR were 0.62 (95%CI, 0.50-0.73), 0.93 (95%CI, 0.90-0.96), and 25.07 (95%CI, 4.28-146.65), respectively. The meta-regression and subgroup analyses found that assessment methods were associated with significant heterogeneity, and quantitative or semiquantitative elastosonography performed better than the qualitative one. Conclusions: Elastosonography showed a limited value for diagnosing malignant salivary gland tumors; it could be considered as a supplementary diagnostic technology to conventional ultrasound, and quantitative or semiquantitative elastosonography was superior to the qualitative one.

Ketogenic diet prevents chronic sleep deprivation-induced Alzheimer's disease by inhibiting iron dyshomeostasis and promoting repair via Sirt1/Nrf2 pathway.

Sleep deprivation (SD) is one of the main risk factors for Alzheimer's disease (AD), but the underlying mechanism is still unclear. Ketogenic diet (KD) has been shown widely neuroprotective effects but less known about its effect on SD-induced AD. In the present study, a continuous 21 days SD mouse model with or without KD was established. The changes of cognitive function, pathological hallmarks of AD, ferroptosis, and intracellular signal pathways in mice were detected by Morris water maze, ThS staining, diaminobenzidine (DAB)-enhanced Perls' stain, antioxidant assay, immuno-histochemistry, and western blot. The results showed that KD can prevent the cognitive deficiency, amyloid deposition and hyperphosphorylated tau induced by chronic SD. Analysis of ferroptosis revealed that KD can inhibit iron dyshomeostasis by down-regulating the expression of TfR1 and DMT1 and up-regulating the expression of FTH1, FPN1. Meanwhile, KD alleviated oxidative stress with elevated xCT/GPX4 axis, FSP1 and reduced MDA. In addition, KD could promote neuronal repair by enhancing BDNF and DCX. Further studies demonstrated that KD activated Sirt1/Nrf2 signaling pathway in the hippocampus in SD-exposed mice. Our finding firstly suggested that KD could prevent chronic SD-induced AD by inhibiting ferroptosis and improving the neuronal repair ability via Sirt1/Nrf2 signaling pathway.

Development of a series of flurbiprofen and zaltoprofen platinum(IV) complexes with anti-metastasis competence targeting COX-2, PD-L1 and DNA.

To develop new anti-metastasis chemotherapeutic drugs, a series of flurbiprofen (FLP) and zaltoprofen (ZTP) platinum(IV) complexes targeting COX-2, PD-L1 and DNA was prepared and investigated. Complex 2 with dual FLP ligands displays promising antitumor activities in vitro and exhibits much potential in overcoming drug resistance. More importantly, the antitumor evaluation in vivo demonstrates that complex 2 possesses promising inhibition of cancer growth and metastasis simultaneously. Further investigation of the mechanism revealed the multi-specific antitumor function of complex 2. It exerts remarkable DNA damage after reduction to platinum(II) complex, and up-regulates the expression of p53 and γ-H2AX. Then, complex 2 promotes mitochondria-mediated apoptosis effectively by activating the Bcl-2/Bax/caspase3 pathway. Furthermore, inflammation in tumor tissues is restrained by the suppression of enzymes COX-2, MMP-9, NLRP3 and caspase1, which would favor the inhibition of tumor metastasis. Moreover, compound 2 boosts T-cell immunity by restraining PD-L1 expression, and further improving the density of CD3+ and CD8+ T cells in tumor tissues.

Laser-responsive multi-functional nanoparticles for efficient combinational chemo-photodynamic therapy against breast cancer.

Herein, novel laser-responsive multi-functional nanoparticles (NPs-Lip@PTX/CyA/Ce6) were fabricated with bovine serum albumins (BSA) based nanoparticles, which simultaneously carried chemotherapeutic drug paclitaxel (PTX) and P-gp inhibitor cyclosporin A (CyA), as core and photosensitizer agent Chlorin e6 (Ce6) loaded Tf-modified liposomal bilayer as shell. NPs-Lip@PTX/CyA/Ce6 exhibited apparent core-shell structure morphology with particle size of 160.9 ± 1.7 nm and zeta potential of - 26.7 ± 0.6 mV, indicating their excellent stability in aqueous solution. Besides, NPs-Lip@PTX/CyA/Ce6 possessed laser-responsive release profiles upon laser irradiation at specific wavelength, which was favor to exert efficient combinatorial chemo-photodynamic therapy and effectively reverse the multiple drug resistance (MDR). Under laser irradiation, as expected, NPs-Lip@PTX/CyA/Ce6 demonstrated superb intracellular ROS productivity and fantastic in vitro and in vivo anti-cancer therapy effect but absent of systemic toxicity. In conclusion, the nano-drug delivery system would be prospectively applied in clinic as resultful therapeutic tactic for investing compositional chemo-photodynamic therapy synergistically.

Diagnostic value of endobronchial ultrasound elastography for differentiating benign and malignant hilar and mediastinal lymph nodes: a systematic review and meta-analysis.

AIMS: In the present study, a meta-analysis was performed to evaluate the diagnostic value of endobronchial ultrasound (EBUS) elastography for differentiating benign and malignant hilar and mediastinal lymph nodes (LNs). MATERIAL AND METHODS: A comprehensive literature search was carried out through PubMed, Embase, and Cochrane Library. Two authors screened the papers and extracted the data independently and any discrepancies were resolved by discussion. The methodolog-ical quality of each included study was assessed by the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and area under the curve were calculated to evaluate the value of EBUS elastography for hilar and mediastinal LNs. RESULTS: Seventeen studies with the number of 2307 LNs were included. There was significant heterogeneity across the included studies. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio for the diagnosis of hilar and mediastinal LNs by EBUS elastography were 0.90 (95% confidence interval [CI], 0.84-0.94), 0.78 (95% CI, 0.74-0.81), 4.1 (95% CI, 3.4-4.9), 0.12 (95% CI, 0.07-0.21) and 33 (95% CI, 17-64), respectively. Furthermore, area under the curve was calculated to be 0.86 (95% CI, 0.82-0.88). CONCLUSION: EBUS elastography is a valuable technology in the differentiation of benign and malignant hilar and mediastinal LNs and could provide supplementary diagnostic information during endobronchial ultrasound-guided transbronchial needle aspiration. The combination of EBUS elastography and B-mode EBUS could improve the diagnostic accuracy for hilar and mediastinal LNs.